At Epic’s recent UGM conference in Verona, WI, CEO Judy Faulkner painted a very big vision of the future – “One Virtual System Worldwide.” She was speaking to the Epic faithful on where Epic and its customers would travel next, a place in the cosmos leading to dramatic breakthroughs in clinical science by phenotyping the de-identified EHR data of all Epic clients.

A foundational element to that virtual system is a new platform, Cosmos. Cosmos is a hosted data warehouse built on Caboodle stack and will include a hosted version of Epic’s analytics toolset, Slicer-Dicer that researchers can use to explore the data. That would be incredibly cool as today there are about 200 million patients with health data in an Epic EHR.

But there may be a tear in the Cosmos. While this is a new release, today Epic has only convinced a small handful of customers to participate. Healthcare providers, particularly large academic medical centers, may be wary of submitting their data for others to use, even for research.

Just how open that virtual system Judy speaks of is to other, competing healthcare solutions is unclear. To Epic’s credit, over the last few years, they have opened up to a significant degree – at least relative to their past walled garden approach to the market. Today, over 100 third-party apps are now available within their App Orchard and a couple of hundred more are in the wings (for more on exactly what App Orchard can and cannot do, Chilmark recently profiled it in our report on health care app stores). The company is also aggressively looking to create a store for new ML/AI models. Today, over 200 clients have developed some 500+ models that work within Epic and that number grows daily.

The company has also made pretty strong headway on the interoperability front, exchanging some 3.5 million records daily – over a third from non-Epic EHRs. Saw numerous examples in presentations by Epic clients of their use of CareEverywhere to enable care coordination across a heterogeneous EHR network, commonly found among today’s Accountable Care Organizations (ACOs).

Epic C.O.O., Carl Dvorak’s keynote was far more pragmatic focusing on how organizations can derive greater ROI from their Epic EHR through benchmarking. Claiming to have over 700 benchmarks developed to date to measure anything from clinical workflows to an analyst’s use of Epic’s analytics tools, Carl provided some good examples of how an organization can improve workforce performance. With ever tightening margins for most healthcare organizations, this message was well-received.

One of the more curious aspects of UGM this year was the near total lack of discussion on the migration to value-based care. Listening to the Epic presentations, visiting the booths of their various modules, looking over the program guide, one was struck by the sheer dearth of attention to this increasing challenge for provider organizations. A provider CEO did confide to me that during the concurrent CEO forum, this topic was discussed at length. But one has to wonder why Epic chose to seemingly ignore this issue, especially for the rank and file users of Epic.

And despite Epic’s growing openness, it did not sit well with me some of the comments Epic executives made regarding patient access to their data via APIs from third-party apps e.g., Apple’s Health app. Epic’s position is that patients don’t necessarily understand the full ramifications of their data being used by others, via various apps, which may end up in nefarious hands.

Epic – let me make that call. Who has access to my health data is my decision, not yours. Your stance harkens back to old, paternalistic modalities in healthcare that are thankfully fading.

No enterprise software vendor is perfect, Epic is no exception, but at UGM one is always struck by the devotion of its users. This comes down to culture – Epic is a company that really does want to do the right thing, though competitors and others may bristle at what that right thing may be. This is best summed up in a conversation I had with an elderly gentleman from Denmark who is the CIO of one of its regional health systems. He stated quite simply:

“I’ve spent my whole life working in enterprise software. Epic is the first company I have ever worked with that truly wants to do the right thing for the customer – they really listen to our input(s).”

That alone is testament enough as to the continuing success of Epic. Will that sense of mission to do the right thing to improve clients’ success and in turn improve healthcare delivery extend beyond Judy’s tenure? Only time will tell, but I sure hope so.

Blockchain in Healthcare: Enthusiasm is growing, but still a long way to go to realize impact

Key Takeaways:

Blockchain can be useful in healthcare in contexts where there is dependency between transactions and an asset, such as data, passes from one party to another.

Some of the applications most ready for ‘prime-time’ include data sharing between payers and providers.

Over the next decade, blockchain will be a significant part of solutions to interoperability challenges.

The speculative craze around Bitcoin and the Initial Coin Offering (ICO) market for startups in the digital currency and blockchain space has heightened the interest in blockchain beyond the crypto-community and into the mainstream. The speculation in the ICO market has driven investment in these vehicles to reach nearly $7 billion in 2017 virtually dwarfing venture capital for startups across all sectors including healthcare. Among the hundreds of startups in the blockchain ICO count are over 70 dealing with healthcare according to industry observer Vince Kuraitis. But speculative capital rarely translates into long-term sustainability and the disruptive business models that startup founders espouse. Limitations with scalability, transaction speeds, energy consumption have been some of the dominant concerns. This is particularly true in healthcare and we have reached an important point in the evolution of the blockchain space where it is worth pausing to take stock of how blockchain applications are evolving and what specific pain points in health IT can current blockchain infrastructures realistically address.

Blockchain can be valuable in contexts where there is dependency between transactions and an asset, such as data, passes from one party to another. Furthermore, when verification of the integrity or provenance of the data is valuable the immutability and time stamping features that blockchain provides are very useful.

Chilmark Research is releasing our “Market Scan Report (MSR) on “Blockchain in Healthcare” with this goal in mind. We wanted to explore the first generation of use cases and startups in the blockchain space and provide a strong foundation for understanding the potential applications in areas that speak to the core capabilities of blockchain as they relate to payers and providers: identity management, data sharing/exchange, provider directories, patient indices, claims adjudication, supply chains and revenue cycle management. We can think of blockchain as having a role in addressing pain points in the healthcare system where we see some of the following challenges:

When multiple parties have need for a shared source of data or registry to generate transactions across a network of disparate agents or tracking of data use is required (delays in reimbursements to providers are frequently driven by inaccuracies in provider registries used by payers)

Where trust is required (in data, in reliability of agents in the network) to fulfill transactions (a major roadblock for data sharing and care coordination across complex networks) or there is currently a minimal amount of trust across the ecosystem of parties that generate transactions (trust in data shared across providers and transparency in when patient data is changed or updated can help reduce medical errors)

Third parties are used to verify parties in transactions but there may be delays or high transaction costs or administrative costs associated with this intermediary role

All data shared in the system requires high privacy and security standards/regulations to be met for compliance or protecting patient/provider data and patient consent but decentralized control of the data would lead to more effective services

Contexts where there is dependency between transactions and an asset, such as data, passes from one party to another are important areas where blockchain can be valuable. Furthermore, when verification of the integrity or provenance of the data is valuable the immutability and time stamping features that blockchain provides are very useful.

Blockchain Applications in Development

Our research into the current applications in development and most-ready for prime time in the next year include companies working in the following areas of the provider-payer nexus:

Provider data management: use of identity management schemes for creating Master Patient Indices and hashing disparate clinical records for patients into a common patient-held wallet

Proof of Provenance, Tracking and Tracing in supply chains: this leverages experience in commodities, digital assets and food supply chains to provide similar services to prevent fraud, enable serialization of pharmaceutical products and protect the integrity of pharma and hospital supply chains. In some markets, globally, up to 50% of drugs can be counterfeit and create tremendous public health problems

Patient benefits and insurance authorization: automate and keep up to date verification and authentication of patients

Claims adjudication: use of APIs and blockchain to create administrative efficiencies and automation of claims adjudication

Better integration of data beyond the EHR: patient-generated data and social determinants data can potentially be compiled and shared while improving privacy and security as well as more patient control of this data via blockchain applications

Provider Directories: Consortia of providers and payers have an opportunity to create up to date provider network registries and automate this process through blockchain.

We provide brief vendor profiles of consulting firms, large tech providers and startups working in the blockchain space and an analysis of where we see this market going in the coming years. These also include some of the larger consulting and tech firms offering enterprise Blockchain-as-a-Service offerings including IBM, Accenture, Deloitte and T-Systems. The startups profiled include PokitDok, Simply Vital Health, Solve.Care, MedRec, Change Healthcare, Factom. There are also alternatives to blockchain or a growing number of companies that have chosen to develop “blockchain friendly” applications until the blockchain ecosystem reaches a higher level of maturity. Google’s DeepMind Health is using an alternative distributed ledger technology with patient records in the UK’s National Health System after creating an uproar over perceived misuse of patient data without approvals or prior consent. Blockchain offers an auditable way to address this controversy. A supply chain/cybersecurity offering by Cloudface provides an analytics solution for hospital supply chain with plans to create blockchain applications in the near future. There is also growing interest in IOTA’s Tangle for the Internet-of-Things (IoT).

Blockchain as an Enabler of Transformation

One interesting example that emerged at the end of our writing this report was the recently announced Optum-Quest-Humana-MultiPlan blockchain initiative to improve provider directories. This is part of an effort to streamline back-office operations for payers. The initiative was developed to address the problem that arises when claims from providers enter the system and there is a mismatch between the records payers have on providers and the provider identity. Often the payer directories are not up to date and the resulting lack of reconciliation of claims submitted by providers results in delays or non-payment of claims. The initiative will launch a pilot during the summer of 2018. What is important about this initiative is the involvement of multiple stakeholders making it a more salient use-case of blockchain for pain points resulting from lack of coordination and effective sharing of data across multiple companies. We view blockchain as a tool for industry transformation rather than disruption of companies, this is a prime example of how to begin thinking about utilizing blockchain in a transformative manner. Over the next decade, we expect to see fewer discussions of blockchain in isolation and it will be a component alongside the cloud, AI and other technologies used to automate administrative functions and enable more efficient sharing of data.

Over the next decade we expect to see fewer discussions of blockchain in isolation and it will be a component alongside the cloud, AI and other technologies used to automate administrative functions and enable more efficient sharing of data.

Blockchain’s Future

The example above also leads us to how Chilmark Research is beginning to think about the future of blockchain in healthcare. Blockchain is an inherently complex new technology that necessarily involves coordination across networks of stakeholders. This means that blockchain ‘disruption’ of healthcare that solves the interoperability challenge or other major pain points with a single technological quick fix is not anywhere even remotely close on the horizon, but we do believe the full impact of the transformative potential of blockchain will play out over the coming decade. 2018 will see a growing number of pilots and experimentation as the hype of 2016-17 spurred considerable interest.

Even government has gotten involved with a Blockchain Caucus in Congress. The ONC’s white paper challenge and recent Trust Exchange Framework bode well for blockchain’s future as well. Blockchain proponents would be well served in the long run by moving beyond a strict techno-centric approach and developing more robust thinking on managing consortia, governance mechanisms, and the broader cryptoeconomics of blockchain in the context of the health economy. Thinking is lagging on these fronts and the froth around easy money via ICOs in 2017 has not helped matters in developing the critical thinking tools towards long-term success for blockchain in the health IT ecosystem.

For those interested in learning more Chilmark Research will be attending the Second Annual Healthcare Blockchain Summit on June 11-12 in Boston where many of the vendors and use cases we analyze in our report will be represented.

Our favorite post of the year is this one. As analysts, we come together with our propeller hats on to collectively look ahead at the key trends in the year to come in the healthcare sector. While there are any number of predictions one might make for this dynamic market, we will stick to what we know best: Healthcare IT and the broader issues that influence this sector.

Following is our annual Baker’s Dozen. As always, love getting your feedback in the comment section. Let the dialog begin.

Merger & acquisition activity continues; Humana or Cigna acquired.Major mergers and acquisitions that mark the end of 2017 (CVS-Aetna, Dignity Health-CHI and rumored Ascension-Providence) will spill over into 2018. Both Humana and Cigna will be in play, and one of them will be acquired or merged in 2018.

Retail health clinics grow rapidly, accounting for 5 percent of primary care encounters.Hot on the health heels of CVS’ acquisition of Aetna, growth in retail health reignites, albeit off a low overall footprint. By end of 2018, retail health clinic locations will exceed 3,000 and account for ~5% of all primary care encounters; up from 1,800 and ~2%, respectively, in 2015.

Apple buys a telehealth vendor.In a bid to one-up Samsung’s partnership with American Well, and in a bid to establish itself as the first tech giant to disrupt healthcare delivery, Apple will acquire a DTC telehealth vendor in 2018.

Sixty percent of ACOs struggle to break even.Despite investments in population health management (PHM) solutions, payers still struggle with legacy back-end systems that hinder timely delivery of actionable claims data to provider organizations. The best intentions for value-based care will flounder, and 60% of ACOs will struggle to break even. ACO formation will continue to grow, albeit more slowly, to mid-single digits in 2018 to just under 1,100 nationwide (up from 923 as of March 2017).

Every major EHR vendor delivers some level of FHIR support, but write access has to wait until 2019.While some of the major EHR vendors have announced support for write access sometime this year and will definitely deliver this support to their most sophisticated customers, broad-based use of write APIs will happen after 2018. HCOs will be wary about willy-nilly changes to the patient record until they see how the pioneers fare.

Cloud deployment chips away at on-premises and vendor-hosted analytics.True cloud-based deployments from name brand vendors such as AWS and Azure are in the minority today. But their price-performance advantages are undeniable to HIT vendors. Cerner will begin to incent its HealtheIntent customers to cloud host on AWS. Even Epic will dip its toes in the public cloud sometime in 2018, probably with some combination of Healthy Planet, Caboodle, and/or Kit.

True condition management remains outside providers’ orbit.Providers will continue to lag behind payers and self-insured employers in adopting condition management solutions. There are two key reasons why: In particular, CMS reluctance to reimburse virtual Diabetes Prevention Programs, and in general, the less than 5% uptake for the CMS chronic care management billing code. In doing so, providers risk further isolation from value-based efforts to improve outcomes while controlling costs.

Mobile-first becomes dominant platform for over 75% of care management solutions.Mobile accessibility is critical for dynamic care management, especially across the ambulatory sector. More than 75% of provider-focused care management vendors will have an integrated, proprietary mobile application for patients and caregivers by end of 2018. These mobile-enabled solutions will also facilitate collection of patient-reported outcome measures, with 50% of solutions offering this capability in 2018.

Solutions continue to document SDoH but don’t yet account for them.A wide range of engagement, PHM, EHR, and care management solutions will make progress on documenting social determinants of health, but no more than 15% of solutions in 2018 will be able to automatically alter care plan interventions based on SDoH in 2018.

ONC defines enforcement rules for “data blocking,” but potential fines do little to change business dynamics that inhibit data liquidity.The hard iron core of this issue is uncertainty about its real impact. No one know what percentage of patients or encounters are impacted when available data is rendered unavailable – intentionally or unintentionally. Data blocking definitely happen,s but most HCOs will rightly wonder about feds willingness to go after the blockers. The Office of the National Coordinator might actually make some rules, but there will be zero enforcement in 2018.

PHM solution market see modest growth of 5-7%.Providers will pull back on aggressive plans to broadly adopt and deploy PHM solution suites, leading to lackluster growth in the PHM market of 5%to 7% in 2018. Instead, the focus will be on more narrow, specific, business-driven use cases, such as standing up an ACO. In response, provider-centric vendors will pivot to the payer market, which has a ready appetite for PHM solutions, especially those with robust clinical data management capabilities.

In-workflow care gap reminders replace reports and dashboards as the primary way to help clinicians meet quality and utilization goals.This is a case where the threat of alert fatigue is preferable to the reality of report fatigue. Gaps are important, and most clinicians want to address them, but not at the cost of voluminous dashboards or reports. A single care gap that is obvious to the clinician opening a chart is worth a thousand reports or dashboards. By the end of 2018, reports and dashboards will no longer be delivered to front-line clinicians except upon request.

At least two dozen companies gain FDA-approval of products using Machine Learning in clinical decision support, up from half a dozen in 2017.Arterys, Quantitative Insights, Butterfly Network, Zebra Medical Vision, EnsoData, and iCAD all received FDA approval for their AI-based solutions in 2017. This is just the start of AI’s future impact in radiology. Pioneer approvals in 2017 — such as Quantitative Insights’ QuantX Advanced breast CADx software and Arterys’s medical imaging platform — will be joined by many more in 2018 as vendors look to leverage the powerful abilities of AI/ML to reduce labor costs and improve outcomes dependent on digital image analysis.

Across the industry novel provider-payer collaborations have arisen – something we refer to as Convergence. The macro-factor driving this push to convergence is simple; the migration to newer value-based care (VBC) reimbursement models and the rise of consumerism in healthcare.

Convergence comes in many forms ranging from Accountable Care Organizations (ACOs) to provider-owned health plans (payvider) to payer-owned provider networks and the most interesting of all – deep strategic partnerships, including joint ventures (JV), that have arisen between a provider and payer. And we are only just getting started.

Anthem refers to their initial foray in convergence – Vivity Health, the seven-system provider network partnership with California Blue Cross as Convergence 1.0. One of their more recent partnerships with Aurora Health in Wisconsin is referred to as Convergence 2.0.

Aetna has also been an early proponent of convergence with its first JV, Innovation Health, which was established a few years back with Virginia’s Inova Health. Since then, Aetna has announced four additional JVs, (Allina, Banner, Sutter and Texas Health Resources). In each of these instances, Aetna is seeking to partner with a healthcare organization to provide a more seamless and complete healthcare service that will be highly attractive to self-insured employers and individuals buying insurance via an exchange. Aetna EVP, Gary Loveman, who is leading this effort, will be one of our keynote speakers at our Convergence conference next month.

Regardless of whether or not it is Convergence 1.0, 2.0, a deeply binding JV or some other form of convergence, core to the success of any of these strategies rests on the need to have a clear data sharing strategy. The deeper the level of convergence – moving from transactional processes to strategic – the greater the need for data transparency. If the convergence strategy is deep, the sharing of data must likewise be comprehensive to ensure that all parties are working from a “single version of the truth.”

Data sharing will be critical to support the applications and workflows that extend across the converged entity. The shared data asset will also be paramount for establishing mutually agreed to key performance indicators (KPIs) such as quality and costs of delivery care, care variability and administrative actions/burden, etc. These KPIs will help to optimize processes and drive alignment across the converged entity’s health service chain.

But this is where the true challenge to convergence arises.

Much of the data that may be necessary for success, is highly sensitive to one party or the other. If there is a lack of trust between partners a converged strategy will most likely fail. This gets to the core of any convergence strategy – mutual respect and trust is the starting point, followed by a strong desire or need to partner. That need to partner, to collaborate deeply must be shared by all parties.

But well meaning intent and a strong desire to share data in support of a convergence strategy is only the beginning of the process. The hardest step will be to define the rules of data usage requiring a strong, mutually agreed to data governance policy.

In our conversations with countless healthcare organizations, we find time and time again that data governance is one of the most oft overlooked aspects of their data curation and analytics strategy. Therefore, it is not too surprising for us to see the struggles that many an organization is facing today with governance that extends beyond their four walls to include a partner, who may at one time have been a competitor.

There are three simple rules to data governance in a converged strategy.

Ensure parity between the two partnering organizations. If one has the upper hand, data sharing will likely be problematic compromising convergence goals and objectives.

Define upfront what datasets will be required and for what purposes. In addition to what types of data and who is responsible for it, address issues such as latency, usage, quality and purposes for which data will be used.

Place a skilled diplomat in charge of your data governance strategy. Governance tackles “soft issues” such as policies, people, privacy, security and trust, all key skills of one with strong diplomatic skills.

Be you a provider or payer, follow these rules to data governance will go a long way to establishing the trusted foundational framework for your own convergence efforts.